Computer Vision and Radiology for COVID-19 Detection

Ravneet Punia, L. Kumar, Mohd. Mujahid, Rajesh Rohilla
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引用次数: 25

Abstract

COVID-19 is spreading rapidly throughout the world. As of 14 April 2020, 128,000 people died of COVID-19, while 1.99 million cases in 210 countries and territories were reported in 219.747 cases. As the virus spreads at a very high rate, there is a huge shortage of medical testing kits all over the world. The respiratory system is the part of the human body most affected by the virus, so the use of X-rays of the chest may prove to be a more efficient way than the thermal screening of the human body. In this paper, we are trying to develop a method that uses radiology, i.e. X-rays for detecting the novel coronavirus. Along with the paper, we also release a dataset for the research community and further development extracted from various medical research hospital facilities treating COVID-19 patients.
COVID-19检测的计算机视觉和放射学
新冠肺炎疫情正在全球迅速蔓延。截至2020年4月14日,共有12.8万人死于COVID-19, 210个国家和地区报告了199万例病例,共有219.747例病例。由于病毒以非常高的速度传播,世界各地的医疗检测试剂盒严重短缺。呼吸系统是人体受病毒影响最严重的部分,因此使用胸部x射线可能比人体热筛检更有效。在这篇论文中,我们试图开发一种利用放射学,即x射线来检测新型冠状病毒的方法。与论文一起,我们还发布了一个数据集,供研究界和进一步开发,这些数据集是从治疗COVID-19患者的各种医学研究医院设施中提取的。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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